Parallel Workers with CPU and Memory Limited

Introduction

This vignette gives examples how to restrict CPU and memory usage of parallel workers. This can useful for optimizing the performance of the parallel workers, but also lower the risk that they overuse the CPU and memory on the machines they are running on.

Examples

Example: Linux parallel workers with a lower process priority (“nice”)

On Unix, we can run any process with a lower CPU priority using the nice command. This can be used when we want to lower the risk of negatively affecting other users and processes that run on the same machine from our R workers overusing the CPUs by mistake. To achieve this, we can prepend nice to the Rscript call via the rscript argument using. This works both on local and remote Linux machines, e.g.

library(parallelly)
cl <- makeClusterPSOCK(2, rscript = c("nice", "*"))
library(parallelly)
workers <- rep("n1.remote.org", 2)
cl <- makeClusterPSOCK(2, rscript = c("nice", "*"))

The special * value expands to the proper Rscript on the machine where the parallel workers are launched.

Example: Linux parallel workers CPU and memory limited by CGroups

This example launches two parallel workers each limited to 100% CPU quota and 50 MiB of memory using Linux CGroups management. The 100% CPU quota limit constrain each worker to use at most one CPU worth of processing preventing them from overusing the machine, e.g. through unintended nested parallelization. The 50 MiB memory limit is strict - if a worker use more than this, the operating system will terminate the worker instantly.

library(parallelly)
cl <- makeClusterPSOCK(
  2L,
  rscript = c(
    "systemd-run", "--user", "--scope",
    "-p", "CPUQuota=100%",
    "-p", "MemoryMax=50M", "-p", "MemorySwapMax=50M",
    "*"
  )
)

For more details, see man systemd.resource-control.

Example: MS Windows parallel workers with specific CPU affinities

This example, works only on MS Windows machines. It launches four local workers, where two are running on CPU Group #0 and two on CPU Group #1.

library(parallelly)
rscript <- I(c(
  Sys.getenv("COMSPEC"), "/c", 
  "start", "/B",
  "/NODE", cpu_group=NA_integer_, 
  "/AFFINITY", "0xFFFFFFFFFFFFFFFE", 
  "*")
)

rscript["cpu_group"] <- 0
cl_0 <- makeClusterPSOCK(2, rscript = rscript)

rscript["cpu_group"] <- 1
cl_1 <- makeClusterPSOCK(2, rscript = rscript)

cl <- c(cl_0, cl_1)

The special * value expands to the proper Rscript on the machine where the parallel workers are launched.